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Scalable Surrogate Deconvolution for Identification of Partially-Observable Systems and Brain Modeling
For many biophysical systems, direct measurement of all state-variables, in – vivo is not-feasible. Thus, a key challenge in biological modeling and signal processing is to reconstruct the activity and structure of interesting biological systems from indirect measurements. These measurements are oft...
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| Pubblicato in: | J Neural Eng |
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| Autori principali: | , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2020
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7946334/ https://ncbi.nlm.nih.gov/pubmed/32590377 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1088/1741-2552/aba07d |
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